"Machine Learning applied to credit analysis: a Systematic Literature Review"

Pincovsky, Mariana; Falcão, A. L. Eiras; Nunes, Waelson N.; Furtado, Ana Paula; Cunha, Rodrigo C.L.V.

doi:10.23919/cisti52073.2021.9476350

2021 16th Iberian Conference on Information Systems and Technologies (CISTI) 2021

DOI: 10.23919/cisti52073.2021.9476350

|View full text |Cite

"Machine Learning applied to credit analysis: a Systematic Literature Review"

Mariana Pincovsky

A. L. Eiras Falcão

Waelson N. Nunes

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Towards AI Dashboards in Financial Services: Design and Implementation of an AI Development Dashboard for Credit Assessment

Pamuk,

Schumann

2024

MAKE

View full text Add to dashboard Cite

Financial institutions are increasingly turning to artificial intelligence (AI) to improve their decision-making processes and gain a competitive edge. Due to the iterative process of AI development, it is mandatory to have a structured process in place, from the design to the deployment of AI-based services in the finance industry. This process must include the required validation and coordination with regulatory authorities. An appropriate dashboard can help to shape and structure the process of model development, e.g., for credit assessment in the finance industry. In addition, the analysis of datasets must be included as an important part of the dashboard to understand the reasons for changes in model performance. Furthermore, a dashboard can undertake documentation tasks to make the process of model development traceable, explainable, and transparent, as required by regulatory authorities in the finance industry. This can offer a comprehensive solution for financial companies to optimize their models, improve regulatory compliance, and ultimately foster sustainable growth in an increasingly competitive market. In this study, we investigate the requirements and provide a prototypical dashboard to create, manage, compare, and validate AI models to be used in the credit assessment of private customers.

show abstract

Towards AI Dashboards in Financial Services: Design and Implementation of an AI Development Dashboard for Credit Assessment

Pamuk,

Schumann

2024

MAKE

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

"Machine Learning applied to credit analysis: a Systematic Literature Review"

Cited by 1 publication

References 20 publications

Towards AI Dashboards in Financial Services: Design and Implementation of an AI Development Dashboard for Credit Assessment

Towards AI Dashboards in Financial Services: Design and Implementation of an AI Development Dashboard for Credit Assessment

Contact Info

Product

Resources

About